1. Field of the Invention
This invention relates to the positive identification of an individual based on hand geometry, thermal signature, hand orientation, hand position, and/or finger configuration. Contactless Hand Recognition (CHR) can be combined with a contact or contactless token to allow for three factors of authentication: (1) physical identification token, (2) the biometric signature, which can be a video contactless hand geometry, or thermal signature derived from a hand, and (3) a unique position of the hand and fingers known only to the individual.
2. Description of Prior Art
Today's hand recognition systems typically require an individual to insert his hand into a box-type device positioning the hand and each finger between fixed pins on its bottom surface. The band recognition system requires all individuals to make contact or touch a platform. Current state-of-the-art models have several disadvantages: (1) sanitary considerations are associated with an intrusive, contact hand reader: many users express concern and dissatisfaction with current invasive contact systems which require many people to touch the same surface. Germs and other substances can be passed from one person to the next through contacting the same surface. (2) hand recognition with these readers cannot be done quickly, while moving, or from a distance: the user seeking access has to stop his forward motion, place his hand inside a hand reader box, wait for recognition, and then remove his hand before proceeding. (3) susceptibility to spoofing is also a factor since there is typically no liveness testing: imitation hands will pass as well as the user's real hand, or worse yet, the user's hand will pass if not alive.
Current systems use an image acquisition system that comprises a light source, a camera, a single mirror and a flat surface. The user places his right hand, palm facing down, on the flat surface of the device. The five pegs serve as control points for an appropriate placement of the hand of the user. The device also has knobs for the system administrator to change the intensity of the light source and the focal length of the camera. The lone mirror projects the side view of the user's hand onto the camera. The image is captured and features are extracted. Feature extraction involves computing the widths and lengths of the fingers at various locations using the captured image. A template is created and compared to a reference template to determine a match.
Since general hand geometry is not as unique as fingerprints, this biometric approach is typically used to authenticate the identity of an individual rather than identify an individual. Authentication is the one-to-one identity match. One-to-one authentication systems typically require a queuing process to bring up the individual file. A one-to-one identity match example is confirming a person is Joe Smith by retrieving his file containing biometrics information such as hand geometry information and this is compared to the individual claiming to be Joe Smith. Identification, conversely, is a one-to-many match. A one-to-many match example is when a hand geometry live image is compared to the geometry of all biometric files to determine a match. Since biometrics focus on varying images and near-fit matches, one-to-many searches have a greater chance for misidentifying a cooperative user than a one-to-one authentication system.